Improving Sentiment Analysis Performance on Imbalanced Moroccan Dialect Datasets Using Resample and Feature Extraction Techniques by Zineb Nassr, Faouzia Benabbou, Nawal Sael, Touria Hamim

“…This study addresses this gap by exploring the integration of data-balancing techniques with machine learning (ML) methods, specifically investigating the impact of resampling techniques and feature extraction methods, including Term Frequency–Inverse Document Frequency (TF-IDF), Bag of Words (BOW), and N-grams. …”
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Seasonal Tree Height Dynamic Estimation Using Multi-source Remotely Sensed Data in Shenzhen by Hang Song, Xuemei Zhang, Ting Hu, Jinglei Liu, Bing Xu

“…In recent years, the development of machine learning and multi-source remotely sensed technologies has provided new ways to measure tree height. …”
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Deriving Full‐Coverage and Fine‐Scale XCO2 Across China Based on OCO‐2 Satellite Retrievals and CarbonTracker Output by Changpei He, Mingrui Ji, Tao Li, Xinyi Liu, Die Tang, Shifu Zhang, Yuzhou Luo, Michael L. Grieneisen, Zihang Zhou, Yu Zhan

“…While the XCO2 kept increasing, the rate of increase declined from 3.23 to 2.10 ppm/year. The machine learning approach is feasible for downscaling and calibrating the CarbonTracker XCO2 data. …”
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Digital Twin Framework Using Real-Time Asset Tracking for Smart Flexible Manufacturing System by Asif Ullah, Muhammad Younas, Mohd Shahneel Saharudin

“…The combination tackles the problem of asset tracking through Wi-Fi localization using machine-learning algorithms. The methodology utilizes the extensive “UJIIndoorLoc” dataset which consists of data from multiple floors and over 520 Wi-Fi access points. …”
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Automated Bitcoin Trading dApp Using Price Prediction from a Deep Learning Model by Zhi Zhan Lua, Chee Kiat Seow, Raymond Ching Bon Chan, Yiyu Cai, Qi Cao

“…This study proposes a cryptocurrency trading system powered by advanced machine learning (ML) models to address these challenges. …”
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Applying Big Data Based Deep Learning System to Intrusion Detection by Wei Zhong, Ning Yu, Chunyu Ai

“…In order to further enhance the performance of machine learning based IDS, we propose the Big Data based Hierarchical Deep Learning System (BDHDLS). …”
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Distinguishing classes of neuroactive drugs based on computational physicochemical properties and experimental phenotypic profiling in planarians. by Danielle Ireland, Christina Rabeler, Sagar Rao, Rudy J Richardson, Eva-Maria S Collins

“…Classification based on physicochemical properties had comparable accuracy to classification based on planarian profiling, especially with the machine learning models that all had accuracies of 90-100%. …”
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Applications of Gene Expression Programming for Estimating Compressive Strength of High-Strength Concrete by Fahid Aslam, Furqan Farooq, Muhammad Nasir Amin, Kaffayatullah Khan, Abdul Waheed, Arslan Akbar, Muhammad Faisal Javed, Rayed Alyousef, Hisham Alabdulijabbar

“…The results reveal that machine learning proposed adamant accuracy and has elucidated performance in the prediction aspect.…”
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Supervised learning and resampling techniques on DISC personality classification using Twitter information in Bahasa Indonesia by Ema Utami, Irwan Oyong, Suwanto Raharjo, Anggit Dwi Hartanto, Sumarni Adi

“…Using a combination of NLP techniques and machine learning, the authors aim to develop a better approach and more robust model, especially for the Indonesian language. …”
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Empirical Analysis for Improving Food Quality Using Artificial Intelligence Technology for Enhancing Healthcare Sector by S. K. UmaMaheswaran, Gaganpreet Kaur, A. Pankajam, A. Firos, Piyush Vashistha, Vikas Tripathi, Hussien Sobahi Mohammed

“…Different AI technologies such as “Machine Learning (ML),” “Neural Language Processing (NLP),” “Rule-Based Expert Systems (RESs),” “Deep Learning (DL),” and so on are used in healthcare and food industries for big “medical data” analysis. …”
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Novel transfer learning approach for hand drawn mathematical geometric shapes classification by Aneeza Alam, Ali Raza, Nisrean Thalji, Laith Abualigah, Helena Garay, Josep Alemany Iturriaga, Imran Ashraf

“…We introduced a novel machine-learning algorithm CnN-RFc that uses convolution neural networks (CNN) for spatial feature extraction and the random forest classifier for probabilistic feature extraction from image data. …”
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Assistive Devices Analysis for Visually Impaired Persons: A Review on Taxonomy by Sadia Zafar, Muhammad Asif, Maaz Bin Ahmad, Taher M. Ghazal, Tauqeer Faiz, Munir Ahmad, Muhammad Adnan Khan

“…In the second stage, state of the art machine learning techniques process these signals and extract useful information. …”
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Multi-omics analysis reveals that neutrophil extracellular traps related gene TIMP1 promotes CRC progression and influences ferroptosis by Yuzhao Jin, Luyu Liao, Qianping Chen, Bufu Tang, Jin Jiang, Ji Zhu, Minghua Bai

“…Method We jointly screened three major NETs genes through machine learning. Large-sample RNA transcriptome and single-cell transcriptome analysis further confirmed that TIMP1 is a core gene in NETs. …”
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Sensor Image, Anomaly Detection Method for Hydroelectric Dam Structure Using Sensors Measurements and Deep Learning by Van-Phuong Ha, Dinh-Van Nguyen, Trong-Chuong Trinh, Duc-Cuong Quach, Van HuyBui

“…To better prevent future disasters, machine-learning algorithms have been employed. Often, these algorithms are trained on historical sensor data to predict future events. …”
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A study on the global patterns in the design and development of ventricular assist devices: a visualization approach by Ajay K. Sood, A. K. Prasada Rao

“…Future studies can be conducted to explore the use of artificial intelligence and machine learning that can learn from data about patients and then adapt as per the requirements of the patients.…”
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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

“…Diseased people experience severe symptoms in more severe cases. such as shortness of breath, which can lead to respiratory failure and death. Machine learning techniques for detection and classification are commonly used in current medical diagnoses. …”
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Klasifikasi Penyakit Alzheimer Dari Scan Mri Otak Menggunakan Convnext by Yehezkiel Stephanus Austin, Haikal Irfano, Juan Young Christopher, Lintang Cahyaning Sukma, Octo Perdana Putra, Riyadh Ilham Ardhanto, Novanto Yudistira

“…Penanganan penyakit ini dapat dilakukan melalui deteksi dini untuk meningkatkan kualitas kehidupan pasien melalui perawatan medis yang efisien dan tepat waktu. Teknologi machine learning dan neural network dapat mendukung deteksi dini melalui penggunaan model ConvNeXt yang telah dilatih dengan metode transfer learning menggunakan bobot awal dari ImageNet, dan di-fine-tune untuk mengklasifikasikan empat tingkat keparahan Alzheimer berdasarkan hasil pemindaian MRI otak, yaitu Mild Demented, Moderate Demented, Non Demented, dan Very Mild Demented. …”
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Adapting to evolving MRI data: A transfer learning approach for Alzheimer’s disease prediction by Rosanna Turrisi, Sarthak Pati, Giovanni Pioggia, Gennaro Tartarisco

“…Integrating 3D magnetic resonance imaging (MRI) with machine learning has shown promising results in healthcare, especially in detecting Alzheimer’s Disease (AD). …”
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Network analyses of brain tumor multiomic data reveal pharmacological opportunities to alter cell state transitions by Brandon Bumbaca, Jonah R. Huggins, Marc R. Birtwistle, James M. Gallo

“…Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. …”
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ARTIFICIAL INTELLIGENCE AS A TECHNOLOGICAL BASIS OF THE DEVELOPMENT OF BANKS by A. Berdyshev

“…Thanks to the development of machine learning, artificial intelligence and cognitive computing, banks can more quickly process huge amounts of information, build more accurate models that can anticipate the needs of customers, create personalized offers and automate their services. …”
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